The continuing increase in demand for electricity and the integration of renewable energy sources require advanced control strategies to ensure an uninterrupted supply and high energy efficiency. Utilities and network operators control the generation and transport networks to compensate for any difference between production and demand.
The residential sector, essentially consisting of houses and buildings, has great potential to influence the ecological cost reduction in the production of electricity through a process that involves the optimization of facilities and changes in consumer habits. This research focuses on this sector to propose methods to increase energy efficiency.
The objective of this research is to obtain a strategy of energy efficiency in residential users in the city of Quito, through the introduction of artificial intelligence techniques such as the Artificial Neural Networks model RNA.
These techniques of modern mathematics as well RNA are appropriate in the current technological context and offer great potential and accuracy.
The methodology is based on established surveys to determine the behavior of consumption in the residential sector in the city. One typical to indicate the most used at certain times and propose an efficient and environmentally sustainable economic strategy appliances daily curves model is established.